An approach for real-time recognition of online Chinese handwritten sentences

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 模式分析与学习

	An approach for real-time recognition of online Chinese handwritten sentences
	Wang, Da-Han 1; Liu, Cheng-Lin1 ; Zhou, Xiang-Dong 2,3
发表期刊	PATTERN RECOGNITION
	2012-10-01
卷号	45 期号:10 页码:3661-3675
文章类型	Article
摘要	With the advances of handwriting capturing devices and computing power of mobile computers, pen-based Chinese text input is moving from character-based input to sentence-based input. This paper proposes a real-time recognition approach for sentence-based input of Chinese handwriting. The main feature of the approach is a dynamically maintained segmentation-recognition candidate lattice that integrates multiple contexts including character classification, linguistic context and geometric context. Whenever a new stroke is produced, dynamic text line segmentation and character over-segmentation are performed to locate the position of the stroke in text lines and update the primitive segment sequence of the page. Candidate characters are then generated and recognized to assign candidate classes, and linguistic context and geometric context involving the newly generated candidate characters are computed. The candidate lattice is updated while the writing process continues. When the pen lift time exceeds a threshold, the system searches the candidate lattice for the result of sentence recognition. Since the computation of multiple contexts consumes the majority of computing and is performed during writing process, the recognition result is obtained immediately after the writing of a sentence is finished. Experiments on a large database CASIA-OLHWDB of unconstrained online Chinese handwriting demonstrate the robustness and effectiveness of the proposed approach. (C) 2012 Elsevier Ltd. All rights reserved.
关键词	Online Chinese Handwritten Sentence Recognition Real-time Recognition Dynamic Text Line Segmentation Dynamic Over-segmentation Dynamic Candidate Lattice Path Search
WOS标题词	Science & Technology ; Technology
关键词[WOS]	CHARACTER-RECOGNITION ; SPEECH RECOGNITION ; LINE RECOGNITION ; CLASSIFICATION ; SEGMENTATION ; MODEL
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000305845300008
引用统计	被引频次：43[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3093
专题	多模态人工智能系统全国重点实验室_模式分析与学习
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Software, Intelligence Engn Lab, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Software, Comp Sci Lab, Beijing 100190, Peoples R China
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Wang, Da-Han,Liu, Cheng-Lin,Zhou, Xiang-Dong. An approach for real-time recognition of online Chinese handwritten sentences[J]. PATTERN RECOGNITION,2012,45(10):3661-3675.
APA	Wang, Da-Han,Liu, Cheng-Lin,&Zhou, Xiang-Dong.(2012).An approach for real-time recognition of online Chinese handwritten sentences.PATTERN RECOGNITION,45(10),3661-3675.
MLA	Wang, Da-Han,et al."An approach for real-time recognition of online Chinese handwritten sentences".PATTERN RECOGNITION 45.10(2012):3661-3675.